Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario.

IoT (Internet-of-Things)-powered devices can be exploited to connect vehicles to smart city infrastructure, allowing vehicles to share their intentions while retrieving contextual information about diverse aspects of urban viability. In this paper, we place ourselves in a transient scenario in which next-generation vehicles that are able to communicate with the surrounding infrastructure coexist with traditional vehicles with limited or absent IoT capabilities. We focus on intersection management, in particular on reusing existing traffic lights empowered by a new management system. We propose an auction-based system in which traffic lights are able to exchange contextual information with vehicles and other nearby traffic lights with the aim of reducing average waiting times at intersections and consequently overall trip times. We use bid propagation to improve standard vehicle trip times while allowing emergency vehicles to free up the way ahead without needing ad hoc system for such vehicle, only an increase in their budget. The proposed system is then tested against two baselines: the classical Fixed Time Control system currently adopted for traffic lights, and an auction strategy that does not exploit traffic light coordination. We performed a large set of experiments using the well known MATSim transport simulator on both a synthetic Manhattan map and on a map we built of an urban area located in Modena, Northern Italy. Our results show that the proposed approach performs better than the classical fixed time control system and the auction strategy that does not exploit coordination among traffic lights.

Development of a Smart Signalization for Emergency Vehicles.

As the population increases, the number of motorized vehicles on the roads also increases. As the number of vehicles increases, traffic congestion occurs. Traffic lights are used at road junctions, intersections, pedestrian crossings, and other places where traffic needs to be controlled to avoid traffic chaos. Due to traffic lights installed in the city, queues of vehicles are formed on the streets for most of the day, and many problems arise because of this. One of the most important problems is that emergency vehicles, such as ambulances, fire engines, police cars, etc., cannot arrive on time despite traffic priorities. Emergency vehicles such as hospitals and police departments need to reach the scene in a very short time. Time loss is a problem that needs to be addressed, especially for emergency vehicles traveling in traffic. In this study, ambulances, fire brigades, police, etc., respond to emergencies. A solution and a related application have been developed so privileged vehicles can reach their target destination as soon as possible. In this study, a route is determined between the current location of an emergency vehicle and its target location in an emergency. Communication between traffic lights is provided with a mobile application developed specifically for the vehicle driver. In this process, the person controlling the lights can turn on the traffic lights during the passage of vehicles. After the vehicles with priority to pass passed, traffic signaling was normalized via the mobile application. This process was repeated until the vehicle reached its destination.

A Blockchain-Based Authentication Protocol for Cooperative Vehicular Ad Hoc Network.

The efficiency of cooperative communication protocols to increase the reliability and range of transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification and communication security are required to be ensured. Though it is difficult to maintain strong network connections between vehicles because of there high mobility, with the help of cooperative communication, it is possible to increase the communication efficiency, minimise delay, packet loss, and Packet Dropping Rate (PDR). However, cooperating with unknown or unauthorized vehicles could result in information theft, privacy leakage, vulnerable to different security attacks, etc. In this paper, a blockchain based secure and privacy preserving authentication protocol is proposed for the Internet of Vehicles (IoV). Blockchain is utilized to store and manage the authentication information in a distributed and decentralized environment and developed on the Ethereum platform that uses a digital signature algorithm to ensure confidentiality, non-repudiation, integrity, and preserving the privacy of the IoVs. For optimized communication, transmitted services are categorized into emergency and optional services. Similarly, to optimize the performance of the authentication process, IoVs are categorized as emergency and general IoVs. The proposed cooperative protocol is validated by numerical analyses which show that the protocol successfully increases the system throughput and decreases PDR and delay. On the other hand, the authentication protocol requires minimum storage as well as generates low computational overhead that is suitable for the IoVs with limited computer resources.

Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming.

Emergency service providers are supposed to locate ambulances such that in case of emergency patients can be reached in a time-efficient manner. Two fundamental decisions and choices need to be made real-time. First of all immediately after a request emerges an appropriate vehicle needs to be dispatched and send to the requests' site. After having served a request the vehicle needs to be relocated to its next waiting location. We are going to propose a model and solve the underlying optimization problem using approximate dynamic programming (ADP), an emerging and powerful tool for solving stochastic and dynamic problems typically arising in the field of operations research. Empirical tests based on real data from the city of Vienna indicate that by deviating from the classical dispatching rules the average response time can be decreased from 4.60 to 4.01 minutes, which corresponds to an improvement of 12.89%. Furthermore we are going to show that it is essential to consider time-dependent information such as travel times and changes with respect to the request volume explicitly. Ignoring the current time and its consequences thereafter during the stage of modeling and optimization leads to suboptimal decisions.

Driving behaviors associated with emergency service vehicle crashes in the U.S. fire service.

OBJECTIVE: Emergency service vehicle incidents are a leading cause of firefighter fatalities and are also hazardous to civilian road users. Modifiable driving behaviors may be associated with emergency service vehicle incidents. The goal of this study was to use telematics to identify driving behaviors associated with crashes in the fire service. METHODS: Forty-three emergency service vehicles in 2 fire departments were equipped with telematics devices (12 in Department A and 31 in Department B). The devices collected vehicle coordinates, speed, and g forces, which were monitored for exceptions to driving rules established by the fire departments regarding speeding, harsh braking, and hard cornering. Fire department administrative reports were used to identify vehicles involved in crashes and merged with daily telematics data. Penalized logistic regression was used to identify driving rules associated with crashes. Least absolute shrinkage and selection operator (LASSO) regression was used to generate a telematics-based risk index for emergency service vehicle incidents. RESULTS: Nearly 1.1 million km of driving data and 44 crashes were recorded among the 2 departments during the study. Harsh braking was associated with increased odds of crash in Department A (odds ratio [OR] = 2.22; 95% confidence interval [CI], 1.09-4.51) and Department B (OR = 1.55; 95% CI, 1.12-2.15). For every kilometer of nonemergency speeding, the odds of crash increased by 35% in Department A (OR = 1.35; 95% CI, 1.03-1.77) and by over 2-fold in Department B (OR = 2.09; 95% CI, 1.19-3.66). In Department B, hard cornering (OR = 1.14; 95% CI, 1.03-1.26) and emergency speeding (OR = 1.65; 95% CI, 1.06-2.57) were also associated with increased odds of crash. The final LASSO risk index model had a sensitivity of 73% and specificity of 57%. CONCLUSIONS: Harsh braking and excessive speeding were driving behaviors most associated with crash in the fire service. Telematics may be a useful tool for monitoring driver safety in the fire service.

Interventions and controls to prevent emergency service vehicle incidents: A mixed methods review.

BACKGROUND: Emergency service vehicle incidents (ESVI), including crashes, rollovers, and roadside struck-by-incidents, are a leading cause of occupational fatality and injury among firefighters and other emergency responders. Though there are numerous strategies and interventions to prevent ESVIs, the evidence base for these strategies is limited and dispersed. The goal of this study was to gather and present a review of evidence-based ESVI interventions. METHODS: We searched five academic databases for articles published within the last decade featuring interventions to reduce or prevent ESVIs. We interviewed key informants from fire departments serving major metropolitan areas for additional interventions. Interventions from both sources were summarized and data on intervention effectiveness were reported when available. RESULTS: Sixty-five articles were included in the final review and 17 key informant interviews were completed. Most articles focused on vehicle engineering interventions (38%), followed by policy and administration interventions (26%), environmental engineering interventions (19%) and education or training (17%). Most key informants reported policy (49%) and training interventions (29%). Enhanced drivers' training and risk management programs were associated with 19-50% and 19-58% reductions in ESVIs, respectively. CONCLUSIONS: Only a limited number of interventions to address ESVIs had adequate outcome data. Based on the available data, training and risk management approaches may be particularly effective approaches to reducing ESVIs.

Does crash risk increase when emergency vehicles are driving with lights and sirens?

INTRODUCTION: Emergency vehicles, such as police, ambulances, and fire vehicles, need to arrive at the scene of emergencies as quickly as possible, and thus they often travel in emergency mode - using their lights and sirens and often bypassing traffic signals. We examined whether travelling in emergency mode increased crash risk among police, ambulance and fire vehicles. METHODS: We conducted a quasi-induced exposure analysis using data from the Iowa Crash Database for the period of 2005 through 2013. The data are maintained by the Iowa Department of Transportation (IADOT), Office of Driver Services (ODS) and includes all investigating police officer's reports of motor vehicle crashes. The quasi-induced exposure method is an approach to calculate crash risk in the absence of exposure data using vehicles without a contributing cause (did not contribute to the crash) as a proxy for the baseline driving population. RESULTS: From 2005 - 2013, police vehicles were involved in 2406 crashes and ambulances and fire vehicles were involved in 528 crashes. Police vehicles were 1.8 times more likely to crash while driving in emergency mode than usual mode; this was a statistically significant increase. Ambulance and fire vehicles were not more likely to crash in emergency mode compared with usual mode. For police, other factors that contributed to crash risk included gender, age, icy/snowy roads, unpaved roads, and intersections. For ambulances and fire vehicles, other factors that contributed to crash risk included gender, age, weekends, icy/snowy roads and urban locations. CONCLUSION: Crash risk increased when police vehicles drove with lights and sirens but did not increase for ambulance and fire vehicles. Further research is necessary to develop and evaluate strategies to mitigate crash risk among police vehicles. Cultural approaches which prioritize transportation safety in conjunction with reaching the scene as quickly as possible may be warranted.